PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A pattern recognition approach for melody track selection in MIDI files
David Rizo, Pedro J. Ponce de León, Carlos Pérez-Sancho, Antonio Pertusa and José Iñesta
In: 7th International Conference on Music Information Retrieval, ISMIR 2006, 8-12 Oct 2006, Victoria, Canada.

Abstract

Standard MIDI files contain data that can be considered as a symbolic representation of music (a digital score), and most of them are structured as a number of tracks. One of them usually contains the melodic line of the piece, while the other tracks contain accompaniment music. The goal of this work is to identify the track that contains the melody using statistical properties of the musical content and pattern recognition techniques. Finding that track is very useful for a number of applications, like speeding up melody matching when searching in MIDI databases or motif extraction, among others. First, a set of descriptors from each track of the target file are extracted. These descriptors are the input to a random forest classifier that assigns the probability of being a melodic line to each track. The track with the highest probability is selected as the one containing the melodic line of that MIDI file. Promising results have been obtained testing a number of databases of different music styles.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:5787
Deposited By:Carlos Pérez-Sancho
Deposited On:08 March 2010